A GIS data processing method and system for geological survey and geochemical exploration

Abstract

The present invention discloses a GIS data processing method and system for geological survey and geochemical exploration, which relates to the technical field of GIS data processing, and solves the technical problems that a large number of raster slices are pre-generated by rasterization of vector data and point cloud data, a large number of raster slices are stored and accessed, which causes system delays, and the access management of multiple data is prone to confusion, affecting the overall data quality; by separating different types of data, it is convenient for more efficient management and retrieval. Each data type has its specific application scenario and processing method, and classified storage helps to quickly locate the required data. Compressing raster and point cloud data and storing them in a cloud server can significantly reduce the storage space occupied and save the storage space of the site, which is especially important for large-scale geographic information systems because these data are often large in size; at the same time, vector data is stored in the corresponding site to facilitate timely retrieval of location data.

Description

Technical Field

[0001] The present invention belongs to the field of GIS data processing, and specifically relates to a method and system for processing GIS data for geological survey and geochemical exploration. Background Art

[0002] With the advancement of science and technology and the increasing demand for geological exploration, traditional geological survey and geochemical exploration methods face many challenges. Traditional methods often rely on manual data collection, paper maps and simple data analysis tools, which are not only inefficient but also difficult to handle large-scale, multi-dimensional data. In addition, environmental changes, resource depletion and attention to sustainable development require modern geological surveys to have more accurate and real-time data support. The rapid development of GIS geographic information system technology has provided new possibilities for solving these problems. GIS can effectively integrate data from different sources, including spatial data such as vectors and rasters, attribute data such as soil composition and mineral content, and three-dimensional point cloud data, to provide a comprehensive perspective on complex geological phenomena. At the same time, GIS also has powerful spatial analysis capabilities, which can help researchers deeply understand the distribution of underground resources and their relationship with the environment.

[0003] Most of the data are stored in a unified manner, and vector data and point cloud data are gridded to pre-generate a large number of raster slices. The storage and access of a large number of raster slices will cause system delays. The access management of multiple data is prone to cause confusion and affect the overall data quality. Summary of the invention

[0004] The present invention aims to solve at least one of the technical problems existing in the prior art; to this end, the present invention proposes a geological survey and geochemical exploration GIS data processing method and system, which are used to solve the technical problems of pre-generating a large number of raster slices by gridding vector data and point cloud data, storing and accessing a large number of raster slices, causing system delays, and access management of multiple data easily causing confusion, affecting the overall data quality.

[0005] To solve the above problems, the first aspect of the present invention provides a method for processing geological survey and geochemical exploration GIS data, comprising:

[0006] Set up several data collection sites in the area of ​​geological survey and geochemical exploration, and ensure that the distance between the sites is greater than the preset threshold; set up GIS data collection equipment at each data collection site, use GPS positioning technology to obtain the location of each site equipment in real time, and mark the site location on the GIS map;

[0007] Import the GIS data of geological survey and geochemical exploration collected at each site into GIS software, and separate the vector data, raster data and point cloud data in the GIS data through GIS software;

[0008] The vector data is directly stored in SVG format and stored in the site's data repository. The raster data and point cloud data are compressed and stored in the cloud server, and the storage address is sent to the corresponding site.

[0009] When a user requests a map of a specific geographic range, the corresponding data is rasterized and raster data is dynamically generated; based on user access data, the access popularity of the raster data is evaluated, and the rasterized slice data of the raster data with access popularity greater than the threshold is cached in the data storage library of the corresponding site;

[0010] Establish the spatial relationship between vector data, raster data and point cloud data, and query the raster data and point cloud data corresponding to the vector data based on the vector data information of the user's query data.

[0011] As a further solution of the present invention: a plurality of data collection sites are set in the area of ​​geological survey and geochemical exploration, and the distance between the sites is ensured to be greater than a preset threshold, including the following steps:

[0012] Obtain map data of the area for geological survey and geochemical exploration through GIS software;

[0013] According to the map data of the area of ​​geological survey and geochemical exploration, the area is divided into: plateau block, plain block, hilly block and river block. The plateau block and plain block are divided into 5000m × 5000m grid units, the hilly block is divided into 4000m × 4000m grid units, and the river block is divided into 8000m × 8000m grid units.

[0014] The GIS software divides the grid cells into different blocks in the GIS map and sets codes for different blocks;

[0015] By extracting grid pixels, the center position is extracted from each grid cell, and a data collection station is set at the center position of each grid cell. According to the block code, a unique number is set for the station in each block.

[0016] As a further solution of the present invention: GIS data collection equipment is set at each data collection site, and the location of each site equipment is obtained in real time through GPS positioning technology, and the site location is marked on the GIS map, including the following steps:

[0017] Set up GIS data collection equipment at each data collection site to collect the site's vector data, raster data, and point cloud data, and add data labels to the data collected at the site according to the site number;

[0018] Extract the location data of the site equipment obtained through GPS positioning technology from the vector data;

[0019] Based on the location data of the site equipment, the site location is marked on the GIS map divided into grid units through GIS software, and the site number is marked;

[0020] The sites in adjacent grid units are connected by straight lines, and a site topology map is drawn on the GIS map.

[0021] As a further solution of the present invention, the GIS data of geological survey and geochemical exploration collected at each site is imported into GIS software, and the vector data, raster data and point cloud data in the GIS data are separated by the GIS software, including the following steps:

[0022] The GIS data of geological survey and geochemical exploration collected at each site, including: vector data, raster data and point cloud data;

[0023] Among them, vector data include: site locations, borehole locations in geological surveys, and sampling point locations in geochemical surveys;

[0024] Raster data, including: geological survey data: underground geological structure data at the drilling location in geological survey; geochemical data: chemical composition data of soil, rock and water at the sampling point in geochemical exploration;

[0025] Point cloud data, including: topographic model of the 2km area around the site;

[0026] Use GIS software to separate vector data, raster data and point cloud data in GIS data.

[0027] As a further solution of the present invention: the vector data is directly stored in SVG format and stored in the data storage library of the site, the raster data and point cloud data are compressed and stored in the cloud server, and the storage address is sent to the corresponding site, including the following steps:

[0028] Convert the vector data into SVG format, store the converted vector data and the site topology map of the corresponding block in the GIS map in the site's data repository, generate a data storage table, record the timestamp of data collection of the vector data in the data storage table, and send the data storage table of the vector data to the cloud server;

[0029] The raster data and point cloud data are compressed and stored in the cloud server, and the timestamps of data acquisition of the raster data and point cloud data are obtained, and the timestamps of the obtained raster data and point cloud data are compared with the timestamps recorded in the data storage table of the vector data, and the raster data and point cloud data with a time difference less than a preset threshold are paired with the vector data;

[0030] The storage addresses of the raster data and point cloud data are sent to the corresponding sites and associated with the paired vector data.

[0031] As a further solution of the present invention: when a user requests a map of a specific geographical range, the corresponding data is rasterized and raster data is dynamically generated, including the following steps:

[0032] When a user requests a map of a specific geographic range, the geographic range parameter in the user request is extracted, and a data storage table is obtained from a site within the geographic range;

[0033] Filter raster data and point cloud data associated with vector data through the site's data storage table;

[0034] The vector point data of the real-time collected site locations in the vector data, the drilling locations in the geological survey, and the sampling point locations in the geochemical exploration are converted into raster format files through the gdal.RasterizeLayer function of the GDAL library;

[0035] The raster format files converted from real-time vector data and the matching raster data are read and merged through the rasterio library to dynamically generate fused rasterized files;

[0036] Reassociate the fused rasterized file with the filtered point cloud data.

[0037] As a further solution of the present invention: evaluating the access popularity of grid data according to user access data, including the following steps:

[0038] By reading the file access log, a user access record table to the raster dataset is established. The raster dataset includes: the raster data stored in the cloud server, and the fused rasterized file corresponding to the raster data;

[0039] The information recorded includes: user ID or IP address, access timestamp, requested dataset name, operation type, and geographic scope;

[0040] Calculate the number of times each raster dataset is accessed within a preset time range, draw a waveform chart of the fluctuation of the number of accesses over time within the preset time range, and count the number of peaks in the number of accesses;

[0041] Perform statistical analysis and evaluate the access popularity of raster data using the following formula:

[0042]

[0043] Among them, r is the access heat evaluation value of the raster data, a1 is the number of times the raster data stored in the cloud server is accessed within the preset time range, a0 is the average number of times all raster data of the corresponding block stored in the cloud server are accessed within the preset time range, a2 is the number of times the fused rasterized file corresponding to the raster data is accessed within the preset time range, c is the number of peaks in the number of accesses counted within the preset time range, and t0 is the duration corresponding to the preset time range.

[0044] As a further solution of the present invention, the rasterized slice data of the raster data with access heat greater than a threshold is cached in a data storage library of the corresponding site, including the following steps:

[0045] Regularly obtain the access heat evaluation value r of the raster data;

[0046] If the access heat evaluation value r of the raster data is greater than 1, the raster data stored in the cloud server and the rasterized slice data of the corresponding fused rasterized file are transferred to the data storage library of the corresponding site for storage, and the storage address of the raster dataset is updated and sent to the corresponding site to be re-associated with the paired vector data;

[0047] If the access heat evaluation value r of the raster data is less than or equal to 1, only the raster data and the rasterized slice data of the corresponding fused rasterized file are stored in the cloud server.

[0048] Establishing the spatial relationship between vector data, raster data and point cloud data, and querying the raster data and point cloud data corresponding to the vector data according to the vector data information of the user's query data, including the following steps:

[0049] Obtain coordinates of site locations in vector data, drill hole locations in geological surveys, and sampling point locations in geochemical surveys;

[0050] Extract data acquisition coordinates from raster data and extract laser radar position coordinates from point cloud data;

[0051] When the distance between the coordinates obtained from the vector data and the coordinates extracted from the raster data and the point cloud data is less than a preset threshold, a spatial index is established between the vector data, the raster data and the point cloud data through a spatial database;

[0052] According to the vector data information of the user's query data, all relevant raster data and point cloud data in the corresponding area are found through the established spatial index.

[0053] As another aspect of the present invention: a geological survey and geochemical exploration GIS data processing system, the system adopts a geological survey and geochemical exploration GIS data processing method as mentioned above to realize geological survey and geochemical exploration GIS data processing.

[0054] Compared with the prior art, the present invention has the following beneficial effects:

[0055] The present invention facilitates more efficient management and retrieval by separating different types of data. Each data type has its specific application scenario and processing method, and classified storage helps to quickly locate the required data. Compressing raster and point cloud data and storing them in the cloud server can significantly reduce the storage space occupied and save the storage space of the site, which is especially important for large-scale geographic information systems because these data are often large in size; raster and point cloud data are stored in the cloud server, which facilitates centralized management and improves data security; at the same time, vector data is stored in the corresponding site to facilitate timely retrieval of location data.

[0056] The present invention caches raster data with high access popularity in a local storage repository, which can significantly shorten the loading time when users request maps and improve user experience. By pre-caching commonly used raster data, complex rasterization processing is avoided for each request, thereby saving computing resources. Only data with access popularity greater than a threshold is cached, which can effectively utilize storage space and focus resources on the most valuable data. It is convenient to periodically evaluate and update the cache content later to ensure that the stored data always has a high access popularity. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0058] Figure 1 It is a schematic diagram of the process of the present invention;

[0059] Figure 2 The present invention is a flow chart of a method for marking site locations in a GIS map. DETAILED DESCRIPTION

[0060] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0061] See also Figure 1-Figure 2 The first embodiment of the present invention provides a method and system for processing geological survey and geochemical exploration GIS data, including:

[0062] Set up several data collection sites in the area of ​​geological survey and geochemical exploration, and ensure that the distance between the sites is greater than the preset threshold; set up GIS data collection equipment at each data collection site, use GPS positioning technology to obtain the location of each site equipment in real time, and mark the site location on the GIS map;

[0063] Import the GIS data of geological survey and geochemical exploration collected at each site into GIS software, such as QGIS software or ArcGIS software, and separate the vector data, raster data and point cloud data in the GIS data through GIS software;

[0064] The vector data is directly stored in SVG format and stored in the site's data repository. The raster data and point cloud data are compressed and stored in the cloud server, and the storage address is sent to the corresponding site.

[0065] When a user requests a map of a specific geographic range, the corresponding data is rasterized and raster data is dynamically generated; based on user access data, the access popularity of the raster data is evaluated, and the rasterized slice data of the raster data with access popularity greater than the threshold is cached in the data storage library of the corresponding site;

[0066] Establish the spatial relationship between vector data, raster data and point cloud data, and query the raster data and point cloud data corresponding to the vector data based on the vector data information of the user's query data.

[0067] In this embodiment, vector data and raster data are stored separately: vector data is directly stored in formats such as SVG and GeoJSON, which are scalable and easy to update. Raster data is stored using more efficient data compression algorithms, such as JPEG2000 and WebP, to reduce storage space.

[0068] Implement on-demand rasterization, that is, rasterization is performed only when a user requests a map of a specific geographic range. Use server-side rendering technology, such as MapServer, GeoServer, etc., to dynamically generate raster data, avoiding the need to pre-generate a large number of rasterized slices for large amounts of data rasterization.

[0069] At the same time, in this embodiment, by setting sites at a certain distance, it is easy to ensure uniform coverage of the entire area, thereby reducing the confusion of sample data and improving the overall data quality. Reasonable distribution of sampling sites can reduce repeated or redundant data collection, saving time and resources.

[0070] Sampling at different locations can reflect the diversity of geological and chemical compositions in the region, providing more comprehensive information for subsequent analysis.

[0071] Using GPS positioning technology, the location of each site can be obtained in real time, making it easier to adjust the sampling strategy as needed. At the same time, real-time data display allows researchers to quickly detect equipment failures or position deviations and make timely adjustments.

[0072] In this embodiment, different types of data are separated to facilitate more efficient management and retrieval. Each data type has its specific application scenario and processing method, and classified storage helps to quickly locate required data.

[0073] Compressing raster and point cloud data and storing them on cloud servers can significantly reduce the storage space occupied and save site storage space, which is especially important for large-scale geographic information systems because these data are often large in size. Storing raster and point cloud data on cloud servers facilitates centralized management and improves data security. At the same time, vector data is stored on the corresponding site to facilitate timely retrieval of location data.

[0074] Store vector data directly in SVG format. Vector data in SVG format is usually smaller than other graphic format files, which can speed up loading and improve user experience.

[0075] In this embodiment, when a user requests a map of a specific geographic range, the corresponding data is rasterized to dynamically generate raster data; based on the user access data, the access popularity of the raster data is evaluated, and the rasterized slice data of the raster data with access popularity greater than a threshold is cached in the data storage library of the corresponding site;

[0076] Caching the most frequently accessed raster data in the local repository can significantly shorten the loading time when users request maps and improve the user experience. By pre-caching commonly used raster data, complex rasterization processing is avoided for each request, thus saving computing resources.

[0077] Only data with access popularity greater than a threshold is cached, which can effectively utilize storage space and focus resources on the most valuable data.

[0078] This facilitates regular evaluation and updating of cache content to ensure that the stored data always has a high access popularity.

[0079] Different sites cache the corresponding frequently accessed raster data to avoid all users accessing the raster data of the cloud server, so that the system can support more user requests at the same time and reduce access delays.

[0080] In this embodiment, a spatial relationship between vector data, raster data, and point cloud data is established, and the raster data and point cloud data corresponding to the vector data are queried according to the vector data information of the user's query data;

[0081] By using spatial databases to build spatial indexes, such as PostGIS, MongoDB, etc., query efficiency can be improved. Structures such as R-tree or Quad tree can be used to organize vector, raster, and point cloud data.

[0082] Determine the grid cells covered by each vector object, and find the corresponding grid cells through intersection operations, such as the ST_Intersects function to find the raster data of the corresponding grid cells.

[0083] Through distance calculation, point cloud objects within a certain range are found and associated with vector features.

[0084] Based on the vector data information provided by the user, use the established spatial index to find all relevant raster and point cloud data in the corresponding area.

[0085] In one embodiment of the present invention, a plurality of data collection sites are set in the area of ​​geological survey and geochemical exploration, and the distance between the sites is ensured to be greater than a preset threshold, including the following steps:

[0086] Obtain map data of the area for geological survey and geochemical exploration through GIS software;

[0087] According to the map data of the area of ​​geological survey and geochemical exploration, the area is divided into: plateau block, plain block, hilly block and river block. The plateau block and plain block are divided into 5000m × 5000m grid units, the hilly block is divided into 4000m × 4000m grid units, and the river block is divided into 8000m × 8000m grid units.

[0088] The GIS software divides the grid cells into different blocks in the GIS map and sets codes for different blocks;

[0089] By extracting grid pixels, the center position is extracted from each grid cell, and a data collection station is set at the center position of each grid cell. According to the block code, a unique number is set for the station in each block.

[0090] In this embodiment, the study area is divided into a uniform grid, and the grid unit size is determined according to a preset threshold value. For example, if the threshold value is 5000 meters, the area can be divided into small squares of 5000 meters×5000 meters.

[0091] A sampling site is selected from the center of each grid cell. This approach ensures that there is a certain spacing between sites.

[0092] According to the actual situation, such as topography, land use, etc., the locations of some stations were adjusted to avoid locations that were not suitable for sampling.

[0093] In one embodiment of the present invention, a GIS data collection device is set at each data collection site, and the location of each site device is obtained in real time through GPS positioning technology, and the site location is marked on the GIS map, including the following steps:

[0094] Set up GIS data collection equipment at each data collection site to collect the site's vector data, raster data, and point cloud data, and add data labels to the data collected at the site according to the site number;

[0095] Extract the location data of the site equipment obtained through GPS positioning technology from the vector data;

[0096] Based on the location data of the site equipment, the site location is marked on the GIS map divided into grid units through GIS software, and the site number is marked;

[0097] The sites in adjacent grid units are connected by straight lines, and a site topology map is drawn on the GIS map.

[0098] In this embodiment, it is ensured that each data collection site is equipped with a GPS positioning device so as to obtain coordinate information in real time.

[0099] Collect data format: Determine the required data format, such as CSV, Shapefile, etc.

[0100] The latitude and longitude coordinates of each data collection site are recorded by the site's GPS equipment.

[0101] Save these coordinates in a table file, such as CSV format, containing fields such as "Site Number", "Longitude", and "Latitude".

[0102] Open your GIS software, start ArcGIS or QGIS, and create a new project.

[0103] Import coordinate data, select "Add layer" or "Import data" in the software, and import the previously saved CSV file.

[0104] Make sure to set the correct coordinate system, usually WGS84.

[0105] Generate a point layer based on the imported data, where each point represents a data collection station.

[0106] Connect the sites in adjacent grid units with straight lines to create a site topology relationship.

[0107] Add site number label display for each site.

[0108] We will handle these steps programmatically using Python and the Geopandas library. The following example demonstrates how to read data from a CSV file and draw a topology graph:

[0109] import pandas as pdimport geopandas as gpdimport matplotlib.pyplot aspltfrom shapely.geometry import Point, LineString

[0110] # Read CSV file

[0111] data = pd.read_csv('stations.csv') # contains 'Name', 'Longitude', 'Latitude' columns

[0112] geometry = [Point(xy) for xy in zip(data['Longitude'], data['Latitude'])]

[0113] gdf_stations = gpd.GeoDataFrame(data, geometry=geometry)

[0114] # Set the coordinate system to WGS84

[0115] gdf_stations.crs = "EPSG:4326"

[0116] # Draw the base map

[0117] world = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres'))

[0118] fig, ax = plt.subplots(figsize=(10, 10))

[0119] world.boundary.plot(ax=ax)

[0120] gdf_stations.plot(ax=ax, color='red', markersize=50)

[0121] #Add label for x, y, label in zip(gdf_stations.geometry.x, gdf_stations.geometry.y, gdf_stations['Name']):

[0122] ax.text(x, y, label)

[0123] # Save the results

[0124] plt.title("Data Collection Stations")

[0125] plt.savefig('topology_map.png')

[0126] plt.show()

[0127] In one embodiment of the present invention, the GIS data of geological survey and geochemical exploration collected at each site is imported into GIS software, and the vector data, raster data and point cloud data in the GIS data are separated by the GIS software, including the following steps:

[0128] The GIS data of geological survey and geochemical exploration collected at each site, including: vector data, raster data and point cloud data;

[0129] Among them, vector data include: site locations, borehole locations in geological surveys, and sampling point locations in geochemical surveys;

[0130] Raster data, including: geological survey data: underground geological structure data at the drilling location in geological survey; geochemical data: chemical composition data of soil, rock and water at the sampling point in geochemical exploration;

[0131] Point cloud data, including: topographic model of the 2km area around the site;

[0132] Use GIS software to separate vector data, raster data and point cloud data in GIS data.

[0133] In one embodiment of the present invention, the vector data is directly stored in SVG format and stored in the data storage library of the site, the raster data and point cloud data are compressed and stored in the cloud server, and the storage address is sent to the corresponding site, including the following steps:

[0134] Convert the vector data into SVG format, store the converted vector data and the site topology map of the corresponding block in the GIS map in the site's data repository, generate a data storage table, record the timestamp of data collection of the vector data in the data storage table, and send the data storage table of the vector data to the cloud server;

[0135] The raster data and point cloud data are compressed and stored in the cloud server, and the timestamps of data acquisition of the raster data and point cloud data are obtained, and the timestamps of the obtained raster data and point cloud data are compared with the timestamps recorded in the data storage table of the vector data, and the raster data and point cloud data with a time difference less than a preset threshold are paired with the vector data;

[0136] The storage addresses of the raster data and point cloud data are sent to the corresponding sites and associated with the paired vector data.

[0137] In one embodiment of the present invention, when a user requests a map of a specific geographic range, the corresponding data is rasterized to dynamically generate raster data, including the following steps:

[0138] When a user requests a map of a specific geographic range, the geographic range parameter in the user request is extracted, and a data storage table is obtained from a site within the geographic range;

[0139] Filter raster data and point cloud data associated with vector data through the site's data storage table;

[0140] The vector point data of the real-time collected site locations in the vector data, the drilling locations in the geological survey, and the sampling point locations in the geochemical exploration are converted into raster format files through the gdal.RasterizeLayer function of the GDAL library;

[0141] The raster format files converted from real-time vector data and the matching raster data are read and merged through the rasterio library to dynamically generate fused rasterized files;

[0142] Reassociate the fused rasterized file with the filtered point cloud data.

[0143] In one embodiment of the present invention, evaluating the access popularity of grid data according to user access data includes the following steps:

[0144] By reading the file access log, a user access record table to the raster dataset is established. The raster dataset includes: the raster data stored in the cloud server, and the fused rasterized file corresponding to the raster data;

[0145] The information recorded includes: user ID or IP address, access timestamp, requested dataset name, operation type, and geographic scope;

[0146] Calculate the number of times each raster dataset is accessed within a preset time range, draw a waveform chart of the fluctuation of the number of accesses over time within the preset time range, and count the number of peaks in the number of accesses;

[0147] Perform statistical analysis and evaluate the access popularity of raster data using the following formula:

[0148]

[0149] Among them, r is the access heat evaluation value of the raster data, a1 is the number of times the raster data stored in the cloud server is accessed within the preset time range, a0 is the average number of times all raster data of the corresponding block stored in the cloud server are accessed within the preset time range, a2 is the number of times the fused rasterized file corresponding to the raster data is accessed within the preset time range, c is the number of peaks in the number of accesses counted within the preset time range, and t0 is the duration corresponding to the preset time range.

[0150] In one embodiment of the present invention, the rasterized slice data of the raster data with access heat greater than a threshold is cached in a data storage library of the corresponding site, including the following steps:

[0151] Regularly obtain the access heat evaluation value r of the raster data;

[0152] If the access heat evaluation value r of the raster data is greater than 1, the raster data stored in the cloud server and the rasterized slice data of the corresponding fused rasterized file are transferred to the data storage library of the corresponding site for storage, and the storage address of the raster dataset is updated and sent to the corresponding site to be re-associated with the paired vector data;

[0153] If the access heat evaluation value r of the raster data is less than or equal to 1, only the raster data and the rasterized slice data of the corresponding fused rasterized file are stored in the cloud server.

[0154] In one embodiment of the present invention, a spatial relationship between vector data, raster data, and point cloud data is established, and according to the vector data information of the user query data, the raster data and point cloud data corresponding to the vector data are queried, including the following steps:

[0155] Obtain coordinates of site locations in vector data, drill hole locations in geological surveys, and sampling point locations in geochemical surveys;

[0156] Extract data acquisition coordinates from raster data and extract laser radar position coordinates from point cloud data;

[0157] When the distance between the coordinates obtained from the vector data and the coordinates extracted from the raster data and the point cloud data is less than a preset threshold, a spatial index is established between the vector data, the raster data and the point cloud data through a spatial database;

[0158] According to the vector data information of the user's query data, all relevant raster data and point cloud data in the corresponding area are found through the established spatial index.

[0159] In another embodiment of the present invention, a geological survey and geochemical exploration GIS data processing system is provided, which uses a geological survey and geochemical exploration GIS data processing method as described above to implement geological survey and geochemical exploration GIS data processing.

[0160] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A method for processing GIS data for geological survey and geochemical exploration, characterized in that: include: Set up several data collection sites in the area of ​​geological survey and geochemical exploration, and ensure that the distance between the sites is greater than the preset threshold; Set up GIS data collection equipment at each data collection site, use GPS positioning technology to obtain the location of each site equipment in real time, and mark the site location on the GIS map; Import the GIS data of geological survey and geochemical exploration collected at each site into GIS software, and separate the vector data, raster data and point cloud data in the GIS data through GIS software; The vector data is directly stored in SVG format and stored in the site's data repository. The raster data and point cloud data are compressed and stored in the cloud server, and the storage address is sent to the corresponding site. When a user requests a map of a specific geographic range, the corresponding data is rasterized and raster data is dynamically generated; According to the user access data, the access popularity of the raster data is evaluated, and the rasterized slice data of the raster data with access popularity greater than the threshold is cached in the data storage library of the corresponding site; Establish the spatial relationship between vector data, raster data and point cloud data, and query the raster data and point cloud data corresponding to the vector data according to the vector data information of the user's query data; The vector data is directly stored in SVG format and stored in the data repository of the site, the raster data and point cloud data are compressed and stored in the cloud server, and the storage address is sent to the corresponding site, including the following steps: Convert the vector data into SVG format, store the converted vector data and the site topology map of the corresponding block in the GIS map in the site's data repository, generate a data storage table, record the timestamp of data collection of the vector data in the data storage table, and send the data storage table of the vector data to the cloud server; The raster data and point cloud data are compressed and stored in the cloud server, and the timestamps of data acquisition of the raster data and point cloud data are obtained, and the timestamps of the obtained raster data and point cloud data are compared with the timestamps recorded in the data storage table of the vector data, and the raster data and point cloud data with a time difference less than a preset threshold are paired with the vector data; The storage addresses of the raster data and point cloud data are sent to the corresponding sites and associated with the paired vector data.

2. A method for processing geological survey and geochemical exploration GIS data according to claim 1, characterized in that: Several data collection sites are set up in the area of ​​geological survey and geochemical exploration, and the distance between the sites is ensured to be greater than the preset threshold, including the following steps: Obtain map data of the area for geological survey and geochemical exploration through GIS software; According to the map data of the area of ​​geological survey and geochemical exploration, the area is divided into: plateau block, plain block, hilly block and river block. The plateau block and plain block are divided into 5000m × 5000m grid units, the hilly block is divided into 4000m × 4000m grid units, and the river block is divided into 8000m × 8000m grid units. The GIS software divides the grid cells into different blocks in the GIS map and sets codes for different blocks; By extracting grid pixels, the center position is extracted from each grid cell, and a data collection station is set at the center position of each grid cell. According to the block code, a unique number is set for the station in each block.

3. A geological survey and geochemical exploration GIS data processing method according to claim 1, characterized in that: Set up GIS data collection equipment at each data collection site, use GPS positioning technology to obtain the location of each site equipment in real time, and mark the site location on the GIS map, including the following steps: Set up GIS data collection equipment at each data collection site to collect the site's vector data, raster data, and point cloud data, and add data labels to the data collected at the site according to the site number; Extract the location data of the site equipment obtained through GPS positioning technology from the vector data; Based on the location data of the site equipment, the site location is marked on the GIS map divided into grid units through GIS software, and the site number is marked; The sites in adjacent grid units are connected by straight lines, and a site topology map is drawn on the GIS map.

4. A method for processing geological survey and geochemical exploration GIS data according to claim 3, characterized in that: Import the GIS data of geological survey and geochemical exploration collected at each site into GIS software, and separate the vector data, raster data and point cloud data in the GIS data through GIS software, including the following steps: The GIS data of geological survey and geochemical exploration collected at each site, including: vector data, raster data and point cloud data; Among them, vector data include: site locations, borehole locations in geological surveys, and sampling point locations in geochemical surveys; Raster data, including: geological survey data: underground geological structure data at the drilling location in geological survey; geochemical data: chemical composition data of soil, rock and water at the sampling point in geochemical exploration; Point cloud data, including: topographic model of the 2km area around the site; Use GIS software to separate vector data, raster data and point cloud data in GIS data.

5. A method for processing geological survey and geochemical exploration GIS data according to claim 1, characterized in that: When a user requests a map of a specific geographic range, the corresponding data is rasterized and raster data is dynamically generated, including the following steps: When a user requests a map of a specific geographic range, the geographic range parameter in the user request is extracted, and a data storage table is obtained from a site within the geographic range; Filter raster data and point cloud data associated with vector data through the site's data storage table; The vector point data of the real-time collected site locations in the vector data, the drilling locations in the geological survey, and the sampling point locations in the geochemical exploration are converted into raster format files through the gdal.RasterizeLayer function of the GDAL library; The raster format files converted from real-time vector data and the matching raster data are read and merged through the rasterio library to dynamically generate fused rasterized files; Reassociate the fused rasterized file with the filtered point cloud data.

6. A method for processing geological survey and geochemical exploration GIS data according to claim 5, characterized in that: Based on user access data, the access popularity of raster data is evaluated, including the following steps: By reading the file access log, a user access record table to the raster dataset is established. The raster dataset includes: the raster data stored in the cloud server, and the fused rasterized file corresponding to the raster data; The information recorded includes: user ID or IP address, access timestamp, requested dataset name, operation type, and geographic scope; Calculate the number of times each raster dataset is accessed within a preset time range, draw a waveform chart of the fluctuation of the number of accesses over time within the preset time range, and count the number of peaks in the number of accesses; Perform statistical analysis and evaluate the access popularity of raster data using the following formula: Among them, r is the access heat evaluation value of the raster data, a1 is the number of times the raster data stored in the cloud server is accessed within the preset time range, a0 is the average number of times all raster data of the corresponding block stored in the cloud server are accessed within the preset time range, a2 is the number of times the fused rasterized file corresponding to the raster data is accessed within the preset time range, c is the number of peaks in the number of accesses counted within the preset time range, and t0 is the duration corresponding to the preset time range.

7. A method for processing geological survey and geochemical exploration GIS data according to claim 6, characterized in that: The rasterized tile data of the raster data with access heat greater than the threshold is cached in the data repository of the corresponding site, including the following steps: Regularly obtain the access heat evaluation value r of the raster data; If the access heat evaluation value r of the raster data is greater than 1, the raster data stored in the cloud server and the rasterized slice data of the corresponding fused rasterized file are transferred to the data storage library of the corresponding site for storage, and the storage address of the raster dataset is updated and sent to the corresponding site to be re-associated with the paired vector data; If the access heat evaluation value r of the raster data is less than or equal to 1, only the raster data and the rasterized slice data of the corresponding fused rasterized file are stored in the cloud server.

8. A method for processing geological survey and geochemical exploration GIS data according to claim 1, characterized in that: Establishing the spatial relationship between vector data, raster data and point cloud data, and querying the raster data and point cloud data corresponding to the vector data according to the vector data information of the user's query data, including the following steps: Obtain coordinates of site locations in vector data, drill hole locations in geological surveys, and sampling point locations in geochemical surveys; Extract data acquisition coordinates from raster data and extract laser radar position coordinates from point cloud data; When the distance between the coordinates obtained from the vector data and the coordinates extracted from the raster data and the point cloud data is less than a preset threshold, a spatial index is established between the vector data, the raster data and the point cloud data through a spatial database; According to the vector data information of the user's query data, all relevant raster data and point cloud data in the corresponding area are found through the established spatial index.

9. A geological survey and geochemical exploration GIS data processing system, characterized in that: The system realizes geological survey and geochemical exploration GIS data processing by using a geological survey and geochemical exploration GIS data processing method as described in any one of claims 1 to 8.

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